1. Field of the Invention
This invention relates to the field of recreating machine operations parameters for monitoring and evaluating an assessment of physical conditions related to machine, environment, and structures.
2. Background Art
Manufacturers have developed systems and methods for predictive and preventive machinery maintenance. Such systems may include a scheduled machine tool change based on a number of parts produced and scheduled machine down time, during which bearings and other components may be replaced prior to their having an adverse effect on product quality. To implement these systems in a cost-effective manner, and to reduce the frequency of these preventative maintenance tasks, decision-makers need to obtain information. In particular, if information indicative of historical trends is useful, accurate predictions can be made regarding future production runs. Also, if the ability to isolate particular problem areas is useful, it helps to concentrate efforts where they will have the most impact and produce the most benefit.
Manufacturers have continued to analyze machine tools and their associated components in an effort to gather information, which they can use to make efficacious decisions regarding their production systems and processes. The types of machine tool analysis are vibration, temperatures, and velocity. Information gathered from these types of analysis may be indicative of a variety of different production problems.
In addition to gathering data indicative of machine operation parameters, it may also be desirable to associate the data with particular operations performed on a machine. Once the data is gathered, it would then be desirable to collect for storage on database that can be subsequently retrieved by one or more remote terminals.
Machine operation parameters refer to a physical property of a machine that is measurable such as temperature, vibration, acceleration, velocity, pressure, liquid level, gas level, gas concentrations, sound, electric field, speed, torque or displacement. Machine requires monitoring spans many industries and includes many types of machines such as mining equipment, draglines, large trucks, industrial robots, over head cranes; heavy industrial equipment such as earth movers; rotating bearings found in factories; rotating machines in steel mills, paper mills, cement factories, petroleum factories, chemical factors, storage facilities; pumps, motors, valves, transformers, generators, centrifuges, and fans. A typical example related to this invention would be monitoring rotating bearings in a paper mill. Another example is monitoring bearings in a mining drag line and stress in an overhead crane. A separate area related to this invention is monitoring the conditions such as temperature, stress or vibration of large structures such as bridges or buildings. In addition, this invention is useful for testing and monitoring of vehicles such as aircraft, spacecraft, or racing cars during normal operations or design phase testing.
Machine operation parameters are typically measured with at least one sensor such as an accelerometer, thermometer probe, gas detector, level detector, velocity probe, displacement probe, pressure sensor, sound level, ultrasonic, humidity probe, corrosion strip, load cell, RTD, proximity sensor, tachometer, or any other suitable sensor capable of sensing a machine operation parameter. Sensors are connected to a concentrator at a central location.
Each type of sensors can vary in form and output and can be coupled to a machine to produce an analog output voltage or current or digital representative of the parameter being measured. A typical sensor produces an analog signal representing a data set of output parameters such as frequency range, voltage range, current range, temperature, impedance, and other electrical, mechanical, or physical properties.
An analyzer converts output analog data collected by the sensor to digital data. The processing steps might include low-pass filtering, high-pass filtering, band-pass filtering, gain adjustment, non-linear adjustments, noise mitigation, zero crossing detection, level detection, or analog to digital conversion, and other types of linear or non linear processing steps. Non-linear adjustments might include distortion correction, limiting, and rectification. It is apparent to those skilled in the art that there are many possible processing steps and many ways to obtain digital data from analog data.
A typical analyzer is a handheld unit that processes and converts the output analog data indicative of machine operation parameters to digital representation format, where it is stored in the analyzer. The analyzer includes detection methods to validate that the sensor is a correct type of sensor, that the sensor is operating correctly, and that the output machine operation parameters are correct. The analyzer might check for shorts or opens in the sensor, lack of output activity, or other fault conditions. In some analyzers the data will be rejected and not stored or marked as bad if the sensor parameters do not appear to be correct.
Some analyzers have extensive analysis capabilities, and can apply various time domain filters and analysis steps. Frequency domain analysis is available in some analyzers, whereby the processed time domain signal can be viewed in the frequency domain, allowing analysis of frequency dependent data. Multiple sensory output data can be collected coherently by an analyzer to produce multi-dimensional plots or to perform multi-dimensional analysis. The analyzer is connected to the concentrator, and a selector is used to connect any one of the sensor channels to the analyzer.
Machine operation parameters collected by an analyzer are typically transmitted via Ethernet, USB, serial port, parallel port, memory cards, portable disk drivers, and wireless network to a data storage unit where the digital data is stored in a database. In some cases, machine operation parameters are collected without the first step of collecting the sensor data into an analyzer; instead, sensory output data is stored directly on a host database server. The host database server is typically a server or mainframe that runs an operating system such as a variety of Windows or Linux, with disk storage for the machine operation parameters and the capability to run analysis programs either locally or remotely (over internet protocol network and wireless network) to analyze the stored output parameters.
A variety of vendors provide collection systems to collect, store and analyze machine operation parameters, and each collection system typically uses a proprietary database to store the output parameters.
Machine operation parameters obtained from one collection system are generally unrecognized by another collection system. Machine operation parameters stored on disk are typically stored in an unpublished and proprietary format, and might be encrypted, or contain specific formatting that is useful to a particular collection system but unrecognized by others.
Likewise, the analyzer from one collection system may not be compatible with another vendor nor is the method for collecting sensory output parameters. A need exists in the art for a method and an apparatus for recreating machine operation parameters collected from varying collection systems to the same characteristics of collected machine operation parameters, so that others may use them to monitor and evaluate the machine operations.